HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
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HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
- by
- Jungil Kong
- Publication date
- 2020-10-14
- Topics
- machine learning, hifi gan, text to speech, vocoder, stt
- Collection
- opensource
- Rights
- MIT license. See LICENSE file in the source zip file
- Item Size
- 1.1G
Contains the paper, a backup of the code and the pre-trained models.
Archived from the following URLs:
Archived from the following URLs:
- https://github.com/jik876/hifi-gan
- https://arxiv.org/abs/2010.05646
- https://drive.google.com/drive/folders/1-eEYTB5Av9jNql0WGBlRoi-WH2J7bp5Y
Notes
Added as part of efforts to keep Voice Cloning App working regardless of the status of files on external hosts.
The g_ models are the generators. These are needed for speech synthesis.
The do_ is the discriminator. This is needed for training.
- Addeddate
- 2024-12-02 01:06:55
- Identifier
- voice-cloning-app-hifigan
- Ocr
- tesseract 5.3.0-6-g76ae
- Ocr_autonomous
- true
- Ocr_detected_lang
- en
- Ocr_detected_lang_conf
- 1.0000
- Ocr_detected_script
- Latin
- Ocr_detected_script_conf
- 1.0000
- Ocr_module_version
- 0.0.21
- Ocr_parameters
- -l eng+Latin
- Page_number_confidence
- 0
- Page_number_module_version
- 1.0.5
- Ppi
- 300
- Scanner
- Internet Archive Python library 5.0.4
- Year
- 2020
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